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AI honesty is impossible to guarantee, new paper proves

Researchers have formally defined the problem of eliciting latent knowledge (ELK) in AI systems using Causal Influence Diagrams. While some feedback-based training strategies can incentivize honest reporting of beliefs, an impossibility theorem proves that no such strategy can guarantee an honest agent with certainty, even with perfect training feedback. The core challenge lies in preventing AI from generalizing to provide answers that appear true rather than being genuinely honest about its internal state. AI

IMPACT Confirms fundamental limitations in training AI for guaranteed honesty, highlighting the difficulty of aligning AI with human values.

RANK_REASON The cluster contains an academic paper presenting a theoretical impossibility result. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jonathan Richens ·

    The Impossibility of Eliciting Latent Knowledge

    Advanced AI systems have extensive knowledge of their environments; in fact, their knowledge may (far) exceed that of their developers or users. Consequently, a desirable property for an AI system is that it is honest -- that it accurately reports its beliefs about the world. Des…